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Materials Data Science

Overview of attention for book
Cover of 'Materials Data Science'

Table of Contents

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    Book Overview
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    Chapter 1 A Brief History of Data and Data Science
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    Chapter 2 From Data Science to Materials Data Science
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    Chapter 3 What You Should Know About Data, Math, and Computing
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    Chapter 4 Materials Science Datasets and Data Generation
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    Chapter 5 Combinatorics and Probabilities
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    Chapter 6 Random Variables and Probability Functions
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    Chapter 7 Expectation, Variance, and Moments
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    Chapter 8 Introduction to Statistics
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    Chapter 9 Exploratory Data Analysis
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    Chapter 10 Commonly Encountered Distributions in Materials Science and Engineering
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    Chapter 11 Introduction and General Concepts of Machine Learning and Data Science
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    Chapter 12 A First Approach to Machine Learning with Linear Regression
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    Chapter 13 Advanced Methods and Topics of Regression
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    Chapter 14 Supervised Classification
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    Chapter 15 Unsupervised Learning
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    Chapter 16 Machine Learning Techniques
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    Chapter 17 From the Perceptron to Artificial Neural Networks
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    Chapter 18 A Gentle Introduction to Deep Learning
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    Chapter 19 Advanced Deep Learning Architectures and Techniques
Attention for Chapter 4: Materials Science Datasets and Data Generation
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Chapter title
Materials Science Datasets and Data Generation
Chapter number 4
Book title
Materials Data Science
Published by
Springer, Cham, January 2024
DOI 10.1007/978-3-031-46565-9_4
Book ISBNs
978-3-03-146564-2, 978-3-03-146565-9
Authors

Sandfeld, Stefan

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Materials Science 1 100%

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